Analysing the Eccentricity of the Air Gap in an Induction Motor Using a Decision Tree Algorithm

This present study presents an air Gap Eccentricity Analysis in Induction Motor utilizing Decision Tree Algorithm. In this study, vibration listening system applied to significance fault study and experimental result shows that vibration and current is ranges of and rotating motor like induction motor for various bearing sins. The industry is very related to the induction motor. Due to allure simple control value, it is also widely used. The unusualness of three-phase initiation motors is mismatched. We knowledgeable speed pulsation, vibration-persuaded acoustic buzz, and friction issues between the stator and rotor on account of the eccentricity issue. The projected methodology is useful on Real- period data and achieves 90% valid Value. The installation of miscellaneous Sensors in order to maintain the Good condition of the inference motor is very priceless. Decision tree algorithm word that modifies a noun detects 90% accurate worth of air gap that is a gap between rotor and stator, also, the LabVIEW tools and capacity analyzer library is secondhand for searching the maximum correct parameter for achieving the result.

Author(s) Details:

Rama Mishra,
Sarvepalli Radhakrishnan University, Bhopal, Madhya Pradesh, India.

E. Vijay Kumar,
Department of Electrical & Electronics, Engineering, Sarvepalli Radhakrishnan University, Bhopal, Madhya Pradesh, India.

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Keywords: Induction motor, spectrum analysis, decision tree algorithm, air gap eccentricity, pattern recognition

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